Poster: Searching For High-Performing Software Configurations With Metaheuristic Algorithms
ICSE (Companion Volume)(2018)
Abstract
Modern systems often have complex configuration spaces. Research has shown that people often just use default settings. This practice leaves significant performance potential unrealized. In this work, we propose an approach that uses metaheuristic search algorithms to explore the configuration space of Hadoop for high-performing configurations. We present results of a set of experiments to show that our approach can find configurations that perform significantly better than defaults. We tested two metaheuristic search algorithms-coordinate descent and genetic algorithms-for three common MapReduce programs-Wordcount, Sort, and Terasort-for a total of six experiments. Our results suggest that metaheuristic search can find configurations cost-effectively that perform significantly better than baseline default configurations.
MoreTranslated text
Key words
configuration, metaheuristic, optimization
AI Read Science
Must-Reading Tree
Example
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined